Blood pressure data processing method and device, and storage medium

Abstract

Disclosed in the examples of the present application are a blood pressure data processing method and device, and a storage medium. The present application is applied to an electronic device, and the electronic device comprises a first system and a second system. The method comprises: in the case of obtaining monitoring data of a plurality of target sampling periods, evaluating, by means of the first system, the monitoring data of one target sampling period or the plurality of target sampling periods to obtain a blood pressure evaluation result corresponding to each of the target sampling periods, wherein the monitoring data comprise data for reflecting the blood pressure of a user; and processing, by means of the second system, the blood pressure evaluation results corresponding to the plurality of target sampling periods to obtain a blood pressure processing result.

Description

Blood pressure data processing method, device, and storage medium

[0001] This application claims priority to the Chinese patent application filed on December 29, 2023, with application number 202311871724.9 and invention name “Blood Pressure Data Processing Method, Device, and Storage Medium”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The embodiments of the present application relate to information processing technology, and relate to but are not limited to a blood pressure data processing method and device, and a storage medium. Background Art

[0003] With the continuous development of technology, people are paying more and more attention to their own health. As an example, people can use electronic devices to monitor their own physiological data and process the physiological data to understand their own health status.

[0004] Therefore, it is of great significance to provide a blood pressure data processing method with low power consumption and accurate measurement. Summary of the Invention

[0005] In a first aspect, an embodiment of the present application provides a blood pressure data processing method, which is applied to an electronic device and includes:

[0006] When monitoring data for multiple target sampling periods is obtained, the first system is used to evaluate and process the monitoring data for one or more target sampling periods to obtain a blood pressure evaluation result corresponding to each target sampling period, wherein the monitoring data includes data used to reflect the user's blood pressure condition;

[0007] The blood pressure assessment results corresponding to multiple target sampling periods are processed by the second system to obtain blood pressure processing results.

[0008] In a second aspect, an embodiment of the present application provides an electronic device, the electronic device including a first system and a second system, the device including:

[0009] When monitoring data for multiple target sampling periods is obtained, the first system is used to evaluate and process the monitoring data for one or more target sampling periods to obtain a blood pressure evaluation result corresponding to each target sampling period, wherein the monitoring data includes data used to reflect the user's blood pressure condition;

[0010] The blood pressure assessment results corresponding to multiple target sampling periods are processed by the second system to obtain blood pressure processing results.

[0011] In a third aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method provided in the embodiment of the present application.

[0012] The blood pressure data processing method, device, and storage medium provided in the embodiments of the present application, when monitoring data of multiple target sampling time periods are obtained, evaluate and process the monitoring data of one or more target sampling time periods through the first system in the electronic device to obtain a blood pressure evaluation result corresponding to each target sampling time period; then, the blood pressure evaluation results corresponding to the multiple target sampling time periods are processed through the second system in the electronic device to obtain a final blood pressure processing result. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The drawings herein are incorporated into and constitute a part of the specification. These drawings illustrate embodiments consistent with the present application and, together with the specification, are used to illustrate the technical solutions of the present application.

[0014] FIG1 is a schematic structural diagram of an electronic device provided in an embodiment of the present application;

[0015] FIG2 is a schematic diagram of an implementation flow of a blood pressure data processing method provided in an embodiment of the present application;

[0016] FIG3 is a schematic diagram of an implementation flow of another blood pressure data processing method provided in an embodiment of the present application;

[0017] FIG4 is a schematic diagram of an implementation flow of extracting characteristic values ​​corresponding to monitoring data of a target sampling period according to an embodiment of the present application;

[0018] FIG5 is a schematic diagram of a heartbeat cycle provided in an embodiment of the present application;

[0019] FIG6 is a schematic diagram of an implementation flow of determining a blood pressure processing result according to an embodiment of the present application;

[0020] FIG7 is a schematic diagram of an implementation flow of another blood pressure data processing method provided in an embodiment of the present application;

[0021] FIG8 is a schematic diagram of an implementation flow of displaying information related to monitoring data and blood pressure conditions according to an embodiment of the present application;

[0022] FIG9 is a schematic diagram of a display interface provided in an embodiment of the present application;

[0023] FIG10 is a schematic diagram of another display interface provided in an embodiment of the present application;

[0024] FIG11 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0025] To make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the specific technical solutions of the present application will be further described in detail below in conjunction with the drawings in the embodiments of the present application. The following embodiments are used to illustrate the present application but are not intended to limit the scope of the present application.

[0026] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0027] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0028] It should be pointed out that the terms "first\second\third" involved in the embodiments of the present application are used to distinguish similar or different objects, and do not represent a specific ordering of the objects. It can be understood that "first\second\third" can be interchanged with a specific order or sequence where permitted, so that the embodiments of the present application described here can be implemented in an order other than that illustrated or described here.

[0029] With the continuous development of technology, people are paying more and more attention to their own health. As an example, people can use electronic devices to monitor their own physiological data and process the physiological data to understand their own health status.

[0030] In the related art, when measuring the blood pressure of users, non-invasive blood pressure data processing methods are mostly used. Non-invasive blood pressure data processing methods can be divided into cuff type and cuffless type. Among them, the cuff type blood pressure data processing method has the advantage of high measurement accuracy, but because blood pressure measurement requires the inflation and deflation of the cuff, it cannot achieve continuous blood pressure detection and is not convenient for long-term use. The cuffless blood pressure data processing method requires continuous collection of blood pressure data, and has high requirements on the power consumption of electronic equipment.

[0031] Therefore, it is of great significance to provide a blood pressure data processing method with low power consumption and accurate measurement.

[0032] In view of this, an embodiment of the present application provides a blood pressure data processing method, which is applied to an electronic device. FIG1 is a diagram illustrating an application scenario of the blood pressure data processing method provided in one embodiment. As shown in FIG1 , a user may carry, wear, or use an electronic device 10.

[0033] The electronic devices involved in the embodiments of the present invention may include general handheld electronic terminals, such as mobile phones, smart phones, portable terminals, terminals, personal digital assistants (PDAs), portable multimedia players (PMPs), laptop computers, notebooks, wireless broadband (Wibro) terminals, tablet computers (personal computers), smart PCs, point of sales (POS) terminals and vehicle-mounted computers.

[0034] Electronic devices may also include wearable devices. Wearable devices are portable electronic devices that can be worn directly on the user or integrated into the user's clothes or accessories. Wearable devices are not just hardware devices, but can also achieve powerful intelligent functions through software support, data interaction, and cloud interaction, such as: computing function, positioning function, alarm function, and can also be connected to mobile phones and various terminals. Wearable devices may include but are not limited to wrist-supported watches (such as watches, wrists, etc.), foot-supported shoes (such as shoes, socks or other leg-worn products), head-supported Glass (such as glasses, helmets, headbands, etc.), as well as smart clothing, backpacks, crutches, accessories and other non-mainstream product forms.

[0035] As shown in FIG1 , the electronic device provided in an embodiment of the present application includes a first system and a second system.

[0036] In some embodiments, the first system and the second system have different power consumptions, that is, when processing the same content, the power consumption of the first system and the power consumption of the second system are different.

[0037] In some embodiments, the computing capabilities of the first system and the second system are different. For example, the computing capabilities of the first system are relatively weak, while the computing capabilities of the second system are relatively strong. The computing capabilities can also be understood as the processing capabilities.

[0038] In some embodiments, the first system may be a first processor, the second system may be a second processor, and both the first processor and the second processor may be microprocessors.

[0039] In some embodiments, the first processor running in the first system is an MCU, and the second processor running in the second system is a CPU.

[0040] If the power consumption of the first system is higher than that of the second system, the first processor corresponding to the first system can be the core processor; if the power consumption of the first system is lower than that of the second system, the second processor corresponding to the second system can be the core processor. The core processor can be understood as the processor corresponding to the system with higher power consumption, or the core processor can also be understood as the processor with greater computing power between the first and second processors.

[0041] In the embodiment of the present application, there is no limitation on the operating timing of the first system and the second system. For example, the first system and the second system can run simultaneously, that is, when the second system runs, the first system also runs; or, the first system and the second system can also have a sequence of running, such as the first system runs first and the second system runs later.

[0042] In some embodiments, the first system can be running while the second system is not running, but the first system must be running simultaneously with the second system. That is, when the first system is in control, the first system can run alone while the second system is not running, which may save power. When the second system is in control, both the first and second systems run, which results in higher power consumption but also greater processing capabilities.

[0043] Here, the first processor and the second processor may include microprocessors configured according to actual applications, and there is no limitation on the operating systems of the first processor and the second processor. For example, the operating system may be Android, Linux, Windows, iOS, RTOS (Real Time Operating System), etc.

[0044] In some embodiments, the first system running on the first processor is an RTOS system, and the second system running on the second processor is an Android system, an IOS system, or a Windows system.

[0045] A communication connection may be established between the first processor and the second processor via a Serial Peripheral Interface (SPI), so that communication data may be transmitted between the first system and the second system via a SPI bus.

[0046] FIG2 is a schematic diagram of the implementation flow of the blood pressure data processing method provided in an embodiment of the present application. The method is applied to the electronic device shown in FIG1 , which includes a first system and a second system. As shown in FIG2 , the method may include the following steps 201 to 202:

[0047] Step 201, when obtaining monitoring data of multiple target sampling periods, evaluate and process the monitoring data of one or more target sampling periods through the first system of the electronic device to obtain the blood pressure evaluation results corresponding to each target sampling period, and the monitoring data includes data used to reflect the user's blood pressure condition.

[0048] In some embodiments, the monitoring data acquired during the multiple target sampling periods may be data used to reflect the user's blood pressure conditions during the multiple target sampling periods.

[0049] For example, the monitoring data may be volume pulse wave data, which is PPG data measured using photoplethysmograph (PPG). Of course, the monitoring data may also be motion data, electrocardiogram (ECG) data, etc. The monitoring data may be acquired using sensors corresponding to the data type.

[0050] In some embodiments, the target sampling period is obtained by screening the monitoring data of multiple initial sampling periods, and the number of monitoring data of the multiple initial sampling periods is greater than or equal to the number of monitoring data of the multiple target sampling periods.

[0051] It is understandable that after acquiring monitoring data from multiple initial sampling periods, not all monitoring data from each initial sampling period will meet the usage requirements. Therefore, in the embodiments of the present application, in order to increase sample availability, reduce abnormal samples, and improve the accuracy of blood pressure processing results, the monitoring data from the multiple initial sampling periods may be screened to obtain monitoring data from multiple target sampling periods.

[0052] In the embodiment of the present application, the method of the screening process is not limited. For example, the screening process may be a process of screening the monitoring data of multiple initial sampling periods according to the time intervals between the multiple initial sampling periods. Alternatively, the screening process may be a process of filtering out abnormal data.

[0053] When the screening process is to screen the monitoring data of multiple initial sampling periods according to the time intervals between the multiple initial sampling periods, the monitoring data of one or more initial sampling periods with a relatively close time interval between the initial sampling periods can be screened out. For example, when the time interval is 0.5 seconds, the initial sampling period 1 is obtained at the 1st second, the initial sampling period 2 is obtained at the 1.5th second, the initial sampling period 3 is obtained at the 2nd second, and so on. In order to avoid excessive computational complexity caused by too much collected data, the data of some initial sampling periods can be removed. For example, any one or more of the initial sampling period 1 obtained at the 1st second, the initial sampling period 2 obtained at the 1.5th second, or the initial sampling period 3 obtained at the 2nd second can be removed.

[0054] To ensure that monitoring data can be obtained within a time period, for example, if the time period is 1 second, the time interval can be set to 0.5 seconds, thereby ensuring that multiple sets of monitoring data can be obtained within the time period. At the same time, to avoid excessive computational complexity caused by excessive data collection, the aforementioned method can be used to remove monitoring data from some sampling periods.

[0055] In some embodiments, in order to avoid redundancy in collected data, if the acquired monitoring data of multiple initial sampling periods are similar, the monitoring data of some initial sampling periods may be removed.

[0056] When the screening process is to filter out abnormal data, the embodiment of the present application does not limit the processing method for filtering out abnormal data. For example, the screening process can be to filter out abnormal values ​​in the monitoring data of each initial sampling period; or, to filter out the monitoring data of the initial sampling period with abnormalities in multiple initial sampling periods; or, based on the data of the gyroscope, accelerometer, etc. in the electronic device, to determine the user's hand movement state, and thus filter out the data with large jitter in the monitoring data of multiple initial sampling periods based on the hand movement state; or, the monitoring data of multiple initial sampling periods can be subjected to mean filtering, baseline drift removal, or high-frequency noise removal.

[0057] The mean filtering method may be a bandpass filter or a sliding average filter, etc. The baseline drift removal and high-frequency noise removal method may be a Gaussian filter, a frequency domain filter, a wavelet transform, etc.

[0058] By screening and processing the monitoring data of multiple initial sampling periods, the influence of the surrounding environment and measuring instruments can be minimized, thereby improving the accuracy of subsequent blood pressure processing results.

[0059] In the embodiment of the present application, there is no limitation on the execution entity for obtaining the monitoring data of multiple target sampling periods.

[0060] For example, in some embodiments, the monitoring data for multiple target sampling periods can be acquired by a data acquisition unit in the electronic device. In other embodiments, the monitoring data for multiple target sampling periods can also be acquired by the first system or the second system. The data acquisition unit and the first system or the second system can be different.

[0061] In some embodiments, when the first system evaluates and processes the monitoring data of one or more target sampling periods to obtain the blood pressure evaluation results corresponding to each target sampling period, it may include evaluating and processing each target sampling period through its own corresponding monitoring data to obtain the corresponding blood pressure evaluation results.

[0062] In some embodiments, when the first system evaluates and processes the monitoring data of one or more target sampling periods to obtain a blood pressure assessment result corresponding to each target sampling period, the system may include, for each target sampling period, using the monitoring data corresponding to the target sampling period itself and the monitoring data of one or more target sampling time periods preceding the target sampling period to obtain the blood pressure assessment result corresponding to the target sampling period. For example, for target sampling period 3, the blood pressure assessment result corresponding to target sampling period 3 may be determined by combining the monitoring data corresponding to the target sampling period itself and the monitoring data corresponding to target sampling period 2 and target sampling period 1 preceding the target sampling period 3.

[0063] In the embodiment of the present application, the method for evaluating and processing the monitoring data of one or more target sampling periods by the first system of the electronic device to obtain the blood pressure evaluation result corresponding to each target sampling period is not limited.

[0064] In some embodiments, the blood pressure assessment result may be presented in the form of a blood pressure assessment score or other parameters, and may be a blood pressure assessment situation characterized by blood pressure-related characteristics during the time period.

[0065] For example, in some embodiments, the characteristic value corresponding to the monitoring data of each target sampling period can be extracted, and the blood pressure assessment result corresponding to each target sampling period can be determined based on the characteristic value. The implementation process can be achieved by referring to steps 301 to 302 in the following embodiment.

[0066] In other embodiments, the blood pressure assessment result corresponding to each target sampling period can be determined by extracting the characteristic value corresponding to the monitoring data of each target sampling period and the user status corresponding to each target sampling period. The implementation process can be achieved by referring to steps 701 to 703 in the following embodiment.

[0067] Step 202 : Processing the blood pressure assessment results corresponding to the multiple target sampling periods through the second system of the electronic device to obtain a blood pressure processing result.

[0068] In the embodiment of the present application, there is no limitation on the method for triggering the second system to process the blood pressure assessment results corresponding to multiple target sampling periods and obtaining the blood pressure processing results.

[0069] For example, in some embodiments, the step of obtaining the blood pressure processing result through the second system may be performed when the number of monitoring data acquired during the multiple target sampling periods meets a preset number.

[0070] In other embodiments, the step of obtaining the blood pressure processing result through the second system may be performed when a processing cycle of the blood pressure processing result obtained through the second system meets a preset period.

[0071] The so-called processing cycle meeting the preset period may include that the time interval between the blood pressure processing result obtained last time through the second system and the blood pressure processing result obtained currently through the second system meets the preset period.

[0072] For example, the preset period is 2 days, and the last blood pressure processing result obtained through the second system was executed on November 12, so the current blood pressure processing result obtained through the second system must be executed on November 14.

[0073] In some other embodiments, when the current time meets the preset time, the step of obtaining the blood pressure processing result through the second system may be executed.

[0074] There is no limitation on the preset time. For example, the preset time may be 10 o'clock. Then, at 10 o'clock every day, the step of obtaining the blood pressure processing result through the second system is executed.

[0075] In some embodiments, when one or more blood pressure assessment results meet a preset result, a step of obtaining a blood pressure processing result through a second system may be performed.

[0076] There is no limitation on the setting of the preset result, which can be set according to actual needs.

[0077] For example, in some embodiments, a preset result of greater than 70 points may be set to indicate that the user's blood pressure is high and may be at risk; and a preset result of less than 40 points may be set to indicate that the user's blood pressure is low and may also be at risk. Thus, if one or more of the multiple blood pressure assessment results meet the preset result, indicating that the user may be at risk, the second system may process the blood pressure assessment results corresponding to each target sampling period to obtain a final blood pressure processing result.

[0078] In some embodiments, when the blood pressure assessment result processed by the first system indicates a risk, the user can be prompted to warn of the risk, and / or the second system can be activated to perform more detailed calculations to provide more comprehensive and accurate results for the user's reference.

[0079] In some embodiments, to obtain the blood pressure processing result, it can be achieved by executing the method described in step 303 of the following embodiment.

[0080] In an embodiment of the present application, on the one hand, by collecting monitoring data reflecting the user's blood pressure status during multiple target sampling periods and integrating the monitoring data of multiple sampling periods to determine the user's blood pressure processing results, the accuracy of the user's blood pressure processing results can be improved; on the other hand, by using a first system and a second system with different power consumption in an electronic device in combination, compared to using a single system to determine the blood pressure processing results, the power consumption of the electronic device can be effectively reduced and the standby time of the electronic device can be increased.

[0081] FIG3 is a schematic diagram of the implementation flow of another blood pressure data processing method provided in an embodiment of the present application. The method is applied to the electronic device shown in FIG1 , which includes a first system and a second system. As shown in FIG3 , the method may include the following steps:

[0082] Step 301 : When monitoring data of multiple target sampling periods are acquired, a characteristic value corresponding to the monitoring data of each target sampling period is acquired through a first system of an electronic device.

[0083] In an embodiment of the present application, the multiple target sampling periods are obtained by screening the monitoring data of the multiple initial sampling periods, and the number of monitoring data of the multiple initial sampling periods is greater than or equal to the number of monitoring data of the multiple target sampling periods.

[0084] The screening process may include screening the multiple initial sampling periods according to the time intervals between the multiple initial sampling periods, or filtering out abnormal data.

[0085] It can be understood that the monitoring data obtained during the target sampling period is generally periodic data, and for each target sampling period, it can be divided into multiple heartbeat cycles to obtain monitoring sub-data corresponding to multiple heartbeat cycles. Considering that a normal person's multiple consecutive heartbeats generally do not undergo particularly drastic changes, it can be assumed that for any feature dimension, all eigenvalues ​​within a target sampling period satisfy the Gaussian distribution, and thus an optimization method (such as the least squares method) is used to fit a Gaussian distribution. In this way, for the monitoring data within a target sampling period, a Gaussian distribution can be obtained for each feature dimension. Each sampling of these Gaussian distributions can generate a set of features, so any number of groups of data can be sampled to more comprehensively characterize the possible essential characteristics of the user during this period, thereby enhancing the diversity of the monitoring data obtained during the target sampling period and improving the accuracy of the blood pressure processing results.

[0086] For example, in some embodiments, extracting the characteristic values ​​corresponding to the monitoring data of the target sampling period can be achieved by executing steps 401 to 403 in the following embodiments:

[0087] Step 401 : Segment the monitoring data of each target sampling period to obtain monitoring sub-data of multiple heartbeat cycles.

[0088] The monitoring data may include one or more of PPG data and ECG data, each of which can reflect the user's heart rate. The cardiac cycle can, to a certain extent, reflect the velocity of the pulse wave within the blood vessels, thereby indirectly reflecting changes in blood pressure, enabling the measurement of the user's blood pressure.

[0089] In some embodiments, the monitoring data of a target sampling period includes at least one heartbeat cycle. Here, the monitoring data of each target sampling period can be segmented to obtain monitoring sub-data of multiple heartbeat cycles.

[0090] In some embodiments, the heartbeat cycle may be a cardiac cycle, which refers to the periodic changes of the heart from the beginning of atrial contraction to the end of ventricular contraction during one heartbeat.

[0091] In some embodiments, after the monitoring data of each target sampling period is segmented to obtain monitoring sub-data of multiple heartbeat cycles, in order to improve the usability of the monitoring sub-data, the monitoring sub-data of the multiple heartbeat cycles may be denoised.

[0092] For example, in some embodiments, a template matching method can be used to detect noise data in the monitoring sub-data of multiple cardiac cycles. By calculating the similarity between the monitoring sub-data of each cardiac cycle and the template data, data with a similarity greater than or equal to a threshold is determined to be non-noise data and retained; data with a similarity less than the threshold is determined to be noise data and removed. The template data can be obtained by averaging the monitoring sub-data of multiple cardiac cycles, or the template data can be the maximum or minimum value of the monitoring sub-data of multiple cardiac cycles, without limitation.

[0093] Step 402: Determine the characteristic value of each heartbeat cycle based on the peak value and trough value of the monitoring sub-data of each heartbeat cycle.

[0094] As can be understood, as shown in Figure 5, a schematic diagram of a heartbeat cycle is provided, and a heartbeat cycle may contain multiple peak values ​​and trough values. The peak values ​​and trough values ​​reflect the waveform changes of the heartbeat cycle to a certain extent, and thus reflect the user's blood pressure.

[0095] Therefore, in an embodiment of the present application, after segmenting and obtaining the monitoring sub-data of multiple heart cycles corresponding to each target sampling period, the peak value and trough value in the monitoring sub-data of each heart cycle under the target sampling period can be extracted, thereby determining the characteristic value of each heart cycle based on the peak value and trough value in each heart cycle.

[0096] In some embodiments, multiple peak values ​​and trough values ​​in each monitoring sub-signal can be used as the first key point of the cardiac cycle; and the maximum value in the first key point and the peak value and trough value in the first key point that are obtained in an order greater than a threshold can be used as the second key point of the cardiac cycle.

[0097] There is no restriction on the setting of obtaining peak values ​​and trough values ​​whose order is greater than the threshold. For example, the first three peak values ​​and the first three trough values ​​can be obtained and used as the second key point.

[0098] Then, the pulse wave analysis (PWA) feature values ​​corresponding to each cardiac cycle are extracted through the above key points.

[0099] Step 403: Obtain characteristic values ​​corresponding to the monitoring data of the corresponding target sampling period according to the characteristic values ​​of the multiple heartbeat cycles included in each target sampling period.

[0100] Here, there is no limitation on the implementation method of obtaining the characteristic values ​​corresponding to the monitoring data of the corresponding target sampling period according to the characteristic values ​​of the multiple heartbeat cycles included in each target sampling period.

[0101] For example, for each target sampling period, the median of the characteristic values ​​of the multiple heartbeat cycles included therein can be calculated, and the median can be used as the characteristic value corresponding to the monitoring data of the target sampling period. Alternatively, for each target sampling period, the mean of the characteristic values ​​of the multiple heartbeat cycles included therein can be used as the characteristic value corresponding to the monitoring data of the target sampling period, etc.

[0102] Step 302: Input the characteristic values ​​corresponding to the monitoring data of each target sampling period into a pre-trained first result evaluation model to obtain the blood pressure evaluation results corresponding to each target sampling period.

[0103] In some embodiments, after obtaining the characteristic values ​​corresponding to the monitoring data of each target sampling period, they can be input into a pre-trained first result evaluation model to train and obtain the blood pressure evaluation results corresponding to the target sampling period.

[0104] The pre-trained first result evaluation model is obtained by training a preset result evaluation model based on historical monitoring data collected within a historical period and historical blood pressure evaluation results corresponding to the historical monitoring data.

[0105] In the embodiments of the present application, there is no limitation on the type of the preset result evaluation model. For example, in some embodiments, considering the interpretability of the algorithm and the resource consumption on the electronic device, a machine learning model of a tree-based algorithm can be selected as the preset result evaluation model.

[0106] Step 303 : Determine the blood pressure processing result according to the blood pressure evaluation result of each target sampling period and the corresponding target weight value through the second system of the electronic device.

[0107] It should be noted that, in some embodiments, the monitoring data obtained for multiple target sampling periods may include monitoring data obtained for multiple target sampling periods within multiple target durations for each day within N days. In some embodiments, the blood pressure assessment result may be presented in the form of a blood pressure assessment score.

[0108] The multiple target sampling periods include a first portion of the target sampling period and a second portion of the target sampling period. The first portion of the target sampling period is a plurality of sampling periods included in the first target duration, and the second portion of the target sampling period is a plurality of sampling periods included in the second target duration.

[0109] For example, the monitoring data for the multiple target sampling periods may include monitoring data for multiple initial sampling periods within multiple target time periods, such as 10:00 AM to 12:00 PM, 2:00 PM to 4:00 PM, and 8:00 PM to 10:00 PM, acquired over three days. There is no limit on the number of initial sampling periods within each target time period; the number of initial sampling periods within different target time periods may be the same or different.

[0110] Furthermore, in some embodiments, in order to obtain more accurate blood pressure processing results, the time intervals between different target durations may be set to be greater than a certain time interval threshold, and the value range of the time interval threshold may include 4 hours to 10 hours, for example, 4 hours, 6 hours, 6.5 hours, or 8 hours, 10 hours, etc., which can be set as needed.

[0111] In the embodiment of the present application, there is no limitation on the method of assigning a corresponding target weight value to the blood pressure assessment result of each target sampling period.

[0112] For example, in some embodiments, the target weight values ​​corresponding to the blood pressure assessment results in each target sampling period may be set to be the same.

[0113] In other embodiments, the sum of the multiple target weight values ​​corresponding to the first part of the target sampling period may be set to be the same as the sum of the multiple target weight values ​​corresponding to the second part of the target sampling period.

[0114] That is to say, assuming that the first target duration includes 100 first target sampling periods and the second target duration includes 50 second target sampling periods, the sum of the target weight values ​​set for the 100 first target sampling periods in the first target duration can be set to be the same as the sum of the target weight values ​​set for the 50 second target sampling periods in the second target duration.

[0115] In this way, we can avoid focusing more on the monitoring data of the target sampling period within a certain target time length, and instead balance the monitoring data of the target sampling period within each target time length, thereby improving the accuracy of the blood pressure assessment results and further improving the accuracy of the blood pressure processing results.

[0116] In the embodiment of the present application, there is no limitation on the type of blood pressure processing result.

[0117] For example, in some embodiments, the blood pressure processing result may include a blood pressure assessment result calculated based on the blood pressure assessment result of each target sampling period and the corresponding target weight value.

[0118] In other embodiments, the blood pressure processing result may include a blood pressure classification result. In this case, the blood pressure processing result may be determined by executing steps 601 to 603 in the following embodiment:

[0119] Step 601 : Determine a candidate evaluation result corresponding to each target sampling period based on the blood pressure evaluation result corresponding to the monitoring data of each target sampling period and the corresponding target weight value.

[0120] Here, the candidate evaluation results may include the product of the blood pressure evaluation result corresponding to the monitoring data of each target sampling period and the corresponding target weight value.

[0121] Step 602: synthesize candidate evaluation results corresponding to multiple target sampling periods to obtain a target evaluation result.

[0122] Here, the target evaluation result may include the weighted average, weighted median, bi-quantile and other results of the candidate evaluation results corresponding to multiple target sampling periods.

[0123] Step 603: Determine the blood pressure classification result based on the target evaluation result and the evaluation threshold. Different blood pressure classification results correspond to different evaluation thresholds.

[0124] Here, the evaluation threshold can be divided into multiple intervals. The evaluation thresholds in different intervals correspond to different blood pressure classification results. The value of each interval can be set according to actual conditions and there is no limitation on this.

[0125] For example, in some embodiments, the evaluation threshold may include a threshold value obtained based on actual experience. Alternatively, in other embodiments, the evaluation threshold may be determined based on physiological data, including at least one of age, weight, gender, and body mass index (BIM).

[0126] In some embodiments, the target evaluation result may be in the form of a target evaluation score, or may be in the form of other features, without limitation.

[0127] It can be understood that by comprehensively considering the physiological data of the user to determine the value of the evaluation threshold, the blood pressure measurement data processing method has a relatively balanced performance for different groups of people and has high stability.

[0128] The blood pressure processing results may be divided into multiple levels of processing results, for example, three levels of processing results, five levels of processing results or more levels of processing results.

[0129] As an example, the multi-level processing results include five levels of processing results, such as hypotension, normotension, high-normal, primary hypertension, and secondary hypertension. High-normal may refer to a value that is slightly higher than the normal range. Hypotension, normotension, high-normal, primary hypertension, and secondary hypertension are the results of comparing the obtained blood pressure processing results with reference thresholds.

[0130] In this way, by dividing the blood pressure into more detailed stratification results, users can pay more attention to their own blood pressure health and facilitate improvements through lifestyle interventions.

[0131] It can be understood that if the user's blood pressure is measured to be normal, it may indicate that the user's health risk during this period is low. Therefore, in order to reduce the power consumption of the device, you can choose to reduce the frequency of collecting its monitoring data; if the user's blood pressure is measured to be abnormal, it may indicate that the user's health risk is high. Therefore, in order to better monitor the user's health, you can choose to increase the frequency of collecting monitoring data.

[0132] Based on this, in some embodiments, when the blood pressure processing result indicates normal blood pressure, the sampling frequency of the monitoring data can be reduced; when the blood pressure processing result indicates abnormal blood pressure, the sampling frequency of the monitoring data can be increased.

[0133] Here, the blood pressure processing result may include a result obtained after processing the blood pressure assessment results corresponding to multiple target sampling time periods; it may also include multiple results obtained after processing the blood pressure assessment results corresponding to multiple target sampling time periods. For example, every 10 blood pressure assessment results can be processed to obtain a blood pressure processing result corresponding to the 10 blood pressure assessment results, thereby obtaining multiple blood pressure processing results.

[0134] Of course, in the case where the blood pressure processing results include multiple blood pressure processing results, the blood pressure processing results characterize abnormal blood pressure, and one of the multiple blood pressure processing results may be abnormal, which indicates that the blood pressure processing result is abnormal; or, in the case where the measurement result characterizing abnormal blood pressure in multiple blood pressure processing results is greater than a threshold, the blood pressure processing result is determined to be abnormal.

[0135] Alternatively, in other embodiments, when the number of blood pressure assessment results indicating normal blood pressure is greater than or equal to a preset threshold value, the sampling frequency of the monitoring data is reduced; when the number of blood pressure assessment results indicating abnormal blood pressure is less than a preset threshold value, the sampling frequency of the monitoring data is increased.

[0136] Here, there is no limitation on the value of the preset quantity threshold, which can be set according to actual needs.

[0137] By implementing this embodiment, the sampling frequency is adjusted in time according to the user's blood pressure condition. When the user's health risk is low, the sampling frequency of the monitoring data is reduced, thereby reducing the power consumption of the device; when the user's health risk is high, the sampling frequency of the monitoring data is increased, thereby strictly monitoring the user's health condition and reducing the user's risk.

[0138] In some embodiments, the blood pressure assessment result can represent a single blood pressure measurement or a short-term blood pressure measurement, such as a single day's blood pressure measurement, while the blood pressure processing result can represent a longer-term blood pressure measurement, such as a long-term blood pressure measurement. This provides users with comprehensive blood pressure monitoring and early warning, from short-term to long-term.

[0139] In an embodiment of the present application, on the one hand, by collecting monitoring data reflecting the user's blood pressure status during multiple target sampling periods and integrating the monitoring data of multiple sampling periods to determine the user's blood pressure processing results, the accuracy of the user's blood pressure processing results can be improved; on the other hand, by using a first system and a second system with different power consumption in an electronic device in combination, compared to using a single system to determine the blood pressure processing results, the power consumption of the electronic device can be effectively reduced and the standby time of the electronic device can be increased.

[0140] FIG7 is a schematic diagram of a flow chart of another blood pressure data processing method provided in an embodiment of the present application. The method is applied to the electronic device shown in FIG1 , which includes a first system and a second system, and the first system and the second system have different power consumption. As shown in FIG7 , the method may include the following steps:

[0141] Step 701 : Acquire monitoring data of multiple target sampling periods, and acquire the user state corresponding to each target sampling period, where the user state includes one or more of a motion state and a sleep state.

[0142] It is understandable that when a user carries or wears an electronic device, they may be in a normal state, exercising, sleeping, etc. The user's corresponding blood pressure value may also be different in different states. For example, the blood pressure value measured when the user is exercising is slightly higher than the blood pressure value measured when the user is sleeping, but this does not mean that the user has high blood pressure during exercise.

[0143] Therefore, in an embodiment of the present application, when acquiring monitoring data of multiple target sampling periods, the user state of the electronic device when collecting monitoring data of each target sampling period can also be acquired, and the user state includes at least motion state and sleep state.

[0144] Likewise, there is no limitation on the execution entity of acquiring the monitoring data of multiple target sampling periods and the user status corresponding to each target sampling period.

[0145] For example, in some embodiments, the monitoring data for multiple target sampling periods and the user status corresponding to each target sampling period can be obtained by a data acquisition unit in the electronic device. In other embodiments, the monitoring data for multiple target sampling periods and the user status corresponding to each target sampling period can also be obtained by the first system or the second system. The data acquisition unit is different from the first system or the second system.

[0146] In some embodiments, the user status corresponding to the target sampling period may also be a type of data in the monitoring data. Thus, when the monitoring data of each target sampling period is obtained, the user status corresponding to the target sampling period may be obtained simultaneously.

[0147] Step 702: Acquire characteristic values ​​corresponding to monitoring data in each target sampling period through the first system of the electronic device.

[0148] In the embodiment of the present application, the method for implementing step 702 is the same as the method for implementing step 302 of the above embodiment of obtaining the characteristic value corresponding to the monitoring data of each target sampling period, and will not be repeated here.

[0149] Step 703: Input the characteristic values ​​corresponding to the monitoring data of each target sampling period and the user status corresponding to each target sampling period into a pre-trained second result evaluation model to obtain the blood pressure evaluation result corresponding to each target sampling period.

[0150] It is understandable that when evaluating the blood pressure evaluation result corresponding to each target sampling period, the evaluation may also be performed based on the detection data of multiple previous target sampling periods and the user status.

[0151] In some embodiments, after obtaining the characteristic values ​​and corresponding user status of the monitoring data of each target sampling period, they can be input into a pre-trained first result evaluation model to train and obtain the blood pressure evaluation results corresponding to the target sampling period.

[0152] Among them, the pre-trained second result evaluation model is obtained by training the preset result evaluation model based on the historical monitoring data collected during the historical period, the user status of the electronic device when the historical monitoring data was collected, and the historical blood pressure evaluation results corresponding to the historical monitoring data.

[0153] In the embodiments of the present application, there is no limitation on the type of the second result evaluation model. For example, in some embodiments, considering the interpretability of the algorithm and the resource consumption on the electronic device, a machine learning model of a tree-based algorithm can be selected as the second result evaluation model.

[0154] Step 704 : Determine a blood pressure processing result based on the blood pressure evaluation result of each target sampling period and the corresponding target weight value through the second system of the electronic device.

[0155] Here, the implementation method of determining the blood pressure processing result may be the same as that described in step 303 of the above embodiment, and will not be repeated here.

[0156] However, it should be noted that, in some embodiments, when the user status corresponding to each target sampling period is obtained, the target weight value corresponding to each target sampling period is related to the user status of the corresponding target sampling period.

[0157] For example, the target weight value of the blood pressure assessment result at the target sampling moment in the exercise state may be set to be smaller than the target weight value of the blood pressure assessment result at the target sampling moment in the normal state of the user.

[0158] In some embodiments, the weight of the monitoring data corresponding to the target sampling time period can be determined based on the user status corresponding to the target sampling time period, and then the monitoring data and weights of one or more target sampling time periods can be input into a pre-trained second result evaluation model to obtain the blood pressure evaluation result of the current target sampling time period.

[0159] It is understandable that the user status may affect the effect of the monitoring data. In some states, the monitoring data may not be suitable as an evaluation parameter, and in some states, its weight needs to be adjusted. In addition, in some embodiments, the blood pressure evaluation result of the current target sampling period needs to be calculated using the monitoring data of multiple previous target sampling periods. Furthermore, the data of each target sampling period must be weighted and adjusted in combination with its user status to make the blood pressure evaluation more accurate. In other words, the user status can be taken into consideration when the first system performs blood pressure evaluation.

[0160] In some embodiments, on the one hand, by collecting monitoring data reflecting the user's blood pressure status during multiple target sampling periods and integrating the monitoring data of multiple sampling periods to determine the user's blood pressure processing results, the accuracy of the user's blood pressure processing results can be improved; on the other hand, by using a first system and a second system with different power consumption in an electronic device in combination, compared to using a single system to determine the blood pressure processing results, the power consumption of the electronic device can be effectively reduced and the standby time of the electronic device can be increased.

[0161] It should be noted that in order to facilitate users to perceive the collection of monitoring data and to facilitate users to manage their own blood pressure, in an embodiment of the present application, relevant monitoring data or blood pressure processing results can also be displayed on the electronic device.

[0162] For example, in some embodiments, the electronic device may further include a display screen, which may establish a communication connection with the first system and the second system and may display data output by the first system or the second system.

[0163] Here, to display information about monitoring data and blood pressure conditions, the following steps 801 to 802 may be performed:

[0164] Step 801, output target information, which includes at least one of the total number of all monitoring data, the number of invalid monitoring data, the number of valid monitoring data, the ratio of invalid monitoring data to all monitoring data, and the ratio of valid monitoring data to all monitoring data, where the valid monitoring data is the monitoring data of multiple target sampling periods.

[0165] Here, the valid monitoring data may include monitoring data of a plurality of target sampling periods determined in all monitoring data.

[0166] When classifying all monitoring data, there is no limitation on the classification method.

[0167] In some embodiments, for all acquired monitoring data, valid monitoring data and invalid monitoring data may be determined based on the acquisition time and quantity of all the monitoring data.

[0168] If a valid time range K (for example, 30 days) can be set, then when blood pressure is measured using all acquired monitoring data, in order to avoid the situation where the user's blood pressure status has changed due to the sampling time being too far away from the present, thereby causing inaccurate measurement results, all monitoring data whose sampling period is not within the valid time range can be treated as invalid monitoring data.

[0169] Alternatively, it may be set that the number of monitoring data obtained in one day is not less than M. If the number of monitoring data obtained in one day is less than M, the monitoring data obtained in that day will be regarded as invalid monitoring data.

[0170] Figure 9 shows a schematic diagram of a display interface. As shown in Figure 9, the total number of all monitoring data, the number of invalid monitoring data, and the number of valid monitoring data can be displayed on the display interface of the electronic device.

[0171] That is, the display interface displays the number M of valid monitoring data acquired each day, and displays the days that are invalid because the number of valid monitoring data is less than M.

[0172] The above-mentioned quantities can be displayed using a calendar chart or a time series chart, without limitation.

[0173] FIG10 shows another schematic diagram of a display interface. As shown in FIG10 , the ratio of invalid monitoring data to all monitoring data and the ratio of valid monitoring data to all monitoring data can also be displayed on the display interface of the electronic device.

[0174] The above data can be presented in the form of numerical values, progress bars, circles, etc., without limitation.

[0175] Step 802: When the target information does not meet the corresponding quantity condition, output information for prompting to increase the wearing time.

[0176] Here, there is no limitation on the case where the target information does not meet the corresponding quantity condition. For example, if the number of valid monitoring data collected within one day is less than the quantity threshold, information for prompting to increase the wearing time is output.

[0177] In this way, users can sense which days their wearing conditions are too poor, such as forgetting to wear a watch on weekends or not wearing it on certain nights. By outputting information prompting users to increase the wearing time, users are reminded to wear it for a longer time or at night, so as to speed up the collection of monitoring data and thus speed up the acquisition of blood pressure processing results.

[0178] In some embodiments, when the target sampling period is short, it will affect the calculation of blood pressure. Therefore, when the target sampling period is less than the preset number, the user can be reminded to increase the wearing time or pay attention to the wearing accuracy. The target sampling period can be understood as the period in which valid monitoring data is obtained.

[0179] It should be understood that, although the steps in the above-mentioned flowcharts are shown in sequence according to the instructions of the arrows, these steps are not necessarily performed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the above-mentioned flowcharts may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily to be performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0180] It should be noted that, in the embodiment of the present application, if the above method is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling an electronic device to execute all or part of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM), a magnetic disk or an optical disk. In this way, the embodiment of the present application is not limited to any specific combination of hardware and software.

[0181] An embodiment of the present application provides an electronic device, which may be a server, and its internal structure diagram may be as shown in Figure 11. The electronic device includes a first system and a second system, and the device includes:

[0182] When monitoring data for multiple target sampling periods is obtained, the first system is used to evaluate and process the monitoring data for one or more target sampling periods to obtain a blood pressure evaluation result corresponding to each target sampling period, wherein the monitoring data includes data used to reflect the user's blood pressure condition;

[0183] The blood pressure assessment results corresponding to multiple target sampling periods are processed by the second system to obtain blood pressure processing results.

[0184] In some embodiments, the first system is also used to obtain characteristic values ​​corresponding to the monitoring data of each target sampling period; the characteristic values ​​corresponding to the monitoring data of each target sampling period are input into a pre-trained first result evaluation model to obtain a blood pressure evaluation result corresponding to each target sampling period; the first pre-trained result evaluation model is obtained by training a preset result evaluation model based on historical monitoring data collected within a historical period, the user status of the electronic device when the historical monitoring data was collected, and the historical blood pressure evaluation results corresponding to the historical monitoring data.

[0185] In some embodiments, the electronic device further obtains a user state corresponding to each target sampling period, where the user state includes one or more of a motion state and a sleep state;

[0186] The first system further obtains a characteristic value corresponding to the monitoring data of each target sampling period;

[0187] The characteristic values ​​corresponding to the monitoring data of each target sampling period and the user status corresponding to each target sampling period are input into a pre-trained second result evaluation model to obtain the blood pressure evaluation results corresponding to each target sampling period; the second pre-trained result evaluation model is obtained by training the preset result evaluation model based on the historical monitoring data collected within the historical period, the user status of the electronic device when the historical monitoring data was collected, and the historical blood pressure evaluation results corresponding to the historical monitoring data.

[0188] In some embodiments, the target sampling period is obtained by filtering the monitoring data of multiple initial sampling periods, and the number of monitoring data of the multiple initial sampling periods is greater than or equal to the number of monitoring data of the multiple target sampling periods. The filtering process includes filtering the multiple initial sampling periods according to the time intervals between the multiple initial sampling periods or filtering out abnormal data.

[0189] In some embodiments, the first system is further configured to segment the monitoring data of each target sampling period to obtain monitoring sub-data of multiple heartbeat cycles;

[0190] Determining a characteristic value of each cardiac cycle according to peak values ​​and trough values ​​of the monitoring sub-data of each cardiac cycle;

[0191] According to the characteristic values ​​of the multiple heartbeat cycles included in each target sampling period, the characteristic value corresponding to the monitoring data of the corresponding target sampling period is obtained.

[0192] In some embodiments, the second system is further configured to determine the blood pressure processing result based on the blood pressure assessment result of each target sampling period and the corresponding target weight value.

[0193] In some embodiments, the blood pressure processing result includes a blood pressure classification result, and the second system is further configured to determine a candidate evaluation result corresponding to each target sampling period based on the blood pressure evaluation result corresponding to the monitoring data of each target sampling period and the corresponding target weight value;

[0194] Combining the candidate evaluation results corresponding to the plurality of target sampling periods to obtain a target evaluation result;

[0195] The blood pressure classification result is determined based on the target evaluation result and the evaluation threshold, and different blood pressure classifications correspond to different evaluation thresholds.

[0196] In some embodiments, when the user status corresponding to each target sampling period is acquired, the target weight value corresponding to each target sampling period is related to the user status of the corresponding target sampling period.

[0197] In some embodiments, the multiple target sampling periods include a first part of the target sampling period and a second part of the target sampling period, the first part of the target sampling period is a plurality of sampling periods included in the first target duration, the second part of the target sampling period is a plurality of sampling periods included in the second target duration, and the sum of the multiple target weight values ​​corresponding to the first part of the target sampling period is the same as the sum of the multiple target weight values ​​corresponding to the second part of the target sampling period.

[0198] In some embodiments, the assessment threshold is determined based on physiological data, wherein the physiological data includes at least one of age, weight, gender, and body mass index (BIM).

[0199] In some embodiments, the monitoring data of the multiple target sampling periods are obtained through the first system and / or the second system; the power consumption of the first system and the second system are different, or the computing capabilities of the first system and the second system are different, or the first system runs on a first processor and the second system runs on a second processor, or the first system runs simultaneously when the second system runs.

[0200] In some embodiments, when the blood pressure processing result indicates that the blood pressure is normal, the sampling frequency of the monitoring data is reduced; or,

[0201] In the case where the blood pressure processing result indicates abnormal blood pressure, increasing the sampling frequency of the monitoring data; or,

[0202] When the number of the blood pressure assessment results indicating normal blood pressure is greater than or equal to a preset number threshold, reducing the sampling frequency of the monitoring data; or

[0203] When the number of the blood pressure assessment results indicating abnormal blood pressure is less than the preset number threshold, the sampling frequency of the monitoring data is increased.

[0204] In some embodiments, the second system is further configured to process the blood pressure assessment results corresponding to multiple target sampling periods to obtain a blood pressure processing result when a preset condition is met; wherein the preset condition is met, including one or more of the following: the number of monitoring data meets a preset number;

[0205] The processing period of the blood pressure processing result obtained by the second system meets a preset period;

[0206] The current moment meets the preset moment;

[0207] One or more of the blood pressure assessment results meet a preset result.

[0208] The processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the electronic device is used to store data. The network interface of the electronic device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, the above method is implemented.

[0209] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the method provided in the above embodiment are implemented.

[0210] An embodiment of the present application provides a computer program product comprising instructions, which, when executed on a computer, enables the computer to execute the steps of the method provided in the above method embodiment.

[0211] Those skilled in the art will understand that the structure shown in Figure 11 is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the electronic device to which the scheme of the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0212] It should be noted that the description of the above storage medium and device embodiments is similar to the description of the above method embodiments and has similar beneficial effects as the method embodiments. For technical details not disclosed in the storage medium, storage medium, and device embodiments of this application, please refer to the description of the method embodiments of this application for understanding.

[0213] It should be understood that "one embodiment" or "an embodiment" or "some embodiments" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "in one embodiment" or "in an embodiment" or "in some embodiments" appearing throughout the specification do not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application. The above-mentioned serial numbers of the embodiments of the present application are for description only and do not represent the advantages and disadvantages of the embodiments. The above description of the various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced to each other. For the sake of brevity, they will not be repeated here.

[0214] The term "and / or" in this article is only a description of the association relationship between associated objects, indicating that there can be three relationships. For example, object A and / or object B can mean: object A exists alone, object A and object B exist at the same time, and object B exists alone.

[0215] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0216] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of the modules is merely a logical function division. In actual implementation, there may be other division methods, such as: multiple modules or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or modules can be electrical, mechanical or other forms.

[0217] The modules described above as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules; they may be located in one place or distributed across multiple network units; some or all of the modules may be selected according to actual needs to achieve the purpose of this embodiment.

[0218] In addition, all functional modules in the embodiments of the present application can be integrated into one processing unit, or each module can be a separate unit, or two or more modules can be integrated into one unit; the above-mentioned integrated modules can be implemented in the form of hardware or in the form of hardware plus software functional units.

[0219] Those skilled in the art will understand that all or part of the steps of implementing the above-mentioned method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above-mentioned method embodiment; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM), magnetic disks or optical disks, and other media that can store program codes.

[0220] Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application, or the part that contributes to the relevant technology, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling an electronic device to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROMs, magnetic disks or optical disks.

[0221] The methods disclosed in the several method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

[0222] The features disclosed in the several product embodiments provided in this application can be arbitrarily combined without conflict to obtain new product embodiments.

[0223] The features disclosed in the several method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments or device embodiments.

[0224] The above is merely an embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A blood pressure data processing method, characterized in that, The method is applied to an electronic device, which includes a first system and a second system. The method includes: When monitoring data of multiple target sampling periods is obtained, through the first system, the monitoring data of one or more of the target sampling periods is evaluated and processed to obtain a blood pressure evaluation result corresponding to each target sampling period. The monitoring data includes data for reflecting the user's blood pressure condition. Through the second system, the blood pressure evaluation results corresponding to multiple target sampling periods are processed to obtain a blood pressure processing result.

2. The method according to claim 1, wherein The evaluating and processing the monitoring data of the multiple target sampling periods to obtain a blood pressure evaluation result corresponding to each target sampling period includes: Obtaining a characteristic value corresponding to the monitoring data of each target sampling period; Inputting the characteristic value corresponding to the monitoring data of each target sampling period into a pre-trained first result evaluation model to obtain a blood pressure evaluation result corresponding to each target sampling period. The pre-trained first result evaluation model is obtained by training a preset result evaluation model according to historical monitoring data collected within a historical period and historical blood pressure evaluation results corresponding to the historical monitoring data.

3. The method according to claim 1, wherein The method further includes: Obtaining the user state corresponding to each target sampling period, where the user state includes one or more of a motion state and a sleep state; The evaluating and processing the monitoring data of one or more of the target sampling periods to obtain a blood pressure evaluation result corresponding to each target sampling period includes: Obtaining a characteristic value corresponding to the monitoring data of each target sampling period; Inputting the characteristic value corresponding to the monitoring data of each target sampling period and the user state corresponding to each target sampling period into a pre-trained second result evaluation model to obtain a blood pressure evaluation result corresponding to each target sampling period. The pre-trained second result evaluation model is obtained by training a preset result evaluation model according to historical monitoring data collected within a historical period, the user state of the electronic device when the historical monitoring data is collected, and historical blood pressure evaluation results corresponding to the historical monitoring data.

4. The method according to any one of claims 1 to 3, characterized in that, The target sampling periods are obtained by screening the monitoring data of multiple initial sampling periods. The number of the monitoring data of the multiple initial sampling periods is greater than or equal to the number of the monitoring data of the multiple target sampling periods. The screening process includes screening the monitoring data of the multiple initial sampling periods according to the time intervals between the multiple initial sampling periods or filtering abnormal data.

5. The method according to claim 2 or 3, characterized in that, The obtaining a characteristic value corresponding to the monitoring data of each target sampling period includes: Performing segmentation processing on the monitoring data of each target sampling period to obtain monitoring sub-data of multiple heartbeat cycles; Determining a characteristic value of each heartbeat cycle according to the peak value and trough value of the monitoring sub-data of each heartbeat cycle; Obtaining a characteristic value corresponding to the monitoring data of the corresponding target sampling period according to the characteristic values of multiple heartbeat cycles included in each target sampling period.

6. The method according to claim 1, characterized in that Processing the blood pressure evaluation results corresponding to multiple target sampling periods to obtain a blood pressure processing result, including: Determining the blood pressure processing result according to the blood pressure evaluation result of each target sampling period and the corresponding target weight value.

7. The method according to claim 6, characterized in that, The blood pressure processing result includes a blood pressure grading result. The determining the blood pressure processing result according to the blood pressure evaluation result of each target sampling period and the corresponding target weight value includes: Determining a candidate evaluation result corresponding to each target sampling period according to the blood pressure evaluation result corresponding to the monitoring data of each target sampling period and the corresponding target weight value; Integrating the candidate evaluation results corresponding to multiple target sampling periods to obtain a target evaluation result; Determining the blood pressure grading result according to the target evaluation result and an evaluation threshold, and different blood pressure grading results correspond to different evaluation thresholds.

8. The method according to claim 6, wherein When the user state corresponding to each target sampling period is obtained, the target weight value corresponding to each target sampling period is related to the user state of the corresponding target sampling period.

9. The method according to claim 6, wherein The multiple target sampling periods include a first part of target sampling periods and a second part of target sampling periods. The first part of target sampling periods are multiple sampling periods included in a first target duration, and the second part of target sampling periods are multiple sampling periods included in a second target duration. The sum of the multiple target weight values corresponding to the first part of target sampling periods is the same as the sum of the multiple target weight values corresponding to the second part of target sampling periods.

10. The method according to claim 7, characterized in that The evaluation threshold is determined according to physiological data, and the physiological data includes at least one of age, weight, gender, and body mass index BIM.

11. The method according to claim 1, wherein The method further includes: Obtaining the monitoring data of the multiple target sampling periods through the first system and / or the second system; the power consumptions of the first system and the second system are different, or the computing capabilities of the first system and the second system are different, or the first system runs on a first processor and the second system runs on a second processor, or the first system runs simultaneously when the second system runs.

12. The method according to claim 1, characterized in that, The method further includes: When the blood pressure processing result indicates normal blood pressure, reducing the sampling frequency of the monitoring data; or When the blood pressure processing result indicates abnormal blood pressure, increasing the sampling frequency of the monitoring data; or When the number of blood pressure evaluation results indicating normal blood pressure is greater than or equal to a preset number threshold, reducing the sampling frequency of the monitoring data; or When the number of blood pressure evaluation results indicating abnormal blood pressure is less than the preset number threshold, increasing the sampling frequency of the monitoring data.

13. The method according to claim 1, characterized in that, Processing the blood pressure evaluation results corresponding to multiple target sampling periods through the second system to obtain a blood pressure processing result, including: When preset conditions are met, processing the blood pressure evaluation results corresponding to multiple target sampling periods through the second system to obtain a blood pressure processing result; wherein, the meeting the preset conditions includes one or more of the following: the number of the monitoring data meets a preset number; The processing cycle for obtaining the blood pressure processing result through the second system meets a preset time limit; The current moment meets a preset moment; One or more of the blood pressure assessment results meet a preset result.

14. An electronic device, characterized in that, The electronic device includes a first system and a second system, and the device includes: In the case of obtaining monitoring data for a plurality of target sampling periods, through the first system, the monitoring data for one or more of the target sampling periods is evaluated and processed to obtain a blood pressure assessment result corresponding to each target sampling period, where the monitoring data includes data for reflecting the user's blood pressure condition; Through the second system, the blood pressure assessment results corresponding to a plurality of target sampling periods are processed to obtain a blood pressure processing result.

15. The electronic device according to claim 14, wherein The first system is further configured to obtain a characteristic value corresponding to the monitoring data for each target sampling period; input the characteristic value corresponding to the monitoring data for each target sampling period into a pre-trained first result evaluation model to obtain a blood pressure assessment result corresponding to each target sampling period; the first pre-trained result evaluation model is obtained by training a preset result evaluation model according to historical monitoring data collected during a historical period, the user state of the electronic device when the historical monitoring data was collected, and the historical blood pressure assessment results corresponding to the historical monitoring data.

16. The electronic device according to claim 14, wherein The electronic device further obtains the user state corresponding to each target sampling period, where the user state includes one or more of a motion state and a sleep state; The first system is further configured to obtain a characteristic value corresponding to the monitoring data for each target sampling period; Input the characteristic value corresponding to the monitoring data for each target sampling period and the user state corresponding to each target sampling period into a pre-trained second result evaluation model to obtain a blood pressure assessment result corresponding to each target sampling period; the second pre-trained result evaluation model is obtained by training a preset result evaluation model according to historical monitoring data collected during a historical period, the user state of the electronic device when the historical monitoring data was collected, and the historical blood pressure assessment results corresponding to the historical monitoring data.

17. The electronic device according to claim 15 or 16, characterized in that, The first system is further configured to perform segmentation processing on the monitoring data for each target sampling period to obtain monitoring sub-data for a plurality of heartbeat cycles; Determine the characteristic value for each heartbeat cycle according to the peak value and trough value of the monitoring sub-data for each heartbeat cycle; Obtain the characteristic value corresponding to the monitoring data for the corresponding target sampling period according to the characteristic values of the plurality of heartbeat cycles included in each target sampling period.

18. The electronic device according to claim 15, wherein The second system is further configured to determine the blood pressure processing result according to the blood pressure assessment result for each target sampling period and the corresponding target weight value.

19. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method according to any one of claims 1 to 13.

20. A computer program product comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method according to any one of claims 1 to 13.

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